A model for the dynamics of a protozoan parasite within and between successive host populations

Abstract

S U M M A R YParasite-host systems often include an obligatory environmental stage in the parasite life-cycle, which can be transmitted between successive populations. Complexity even increases if immunity only gradually develops upon re-infection. For a better understanding of such systems we study Eimeria spp. in chickens, a protozoan parasite transmitted through oocysts on the floor. This paper deals with dynamics within and between successive cohorts of chickens by coupling a within-host description of the parasite life-cycle (with immunity) to re-uptake of oocysts from the environment. First the initial environmental oocyst level is related to the maximum infection load within a cohort, as a measure of production damage, from which we conclude that minimum damage levels can be observed with intermediate oocyst levels. Then we relate the initial to the final oocyst level of a cohort, and study the dynamics between cohorts in relation to an oocyst cleaning efficiency after each cohort. The resulting unstable dynamics lead to the conclusion that it will often be impossible to minimize damage by repeatedly cleaning with the same effort: it may be necessary to artificially increase oocyst levels in the shed before each chicken cohort.

The effectiveness of mass vaccination on Marek's disease virus (MDV) outbreaks and detection within a broiler barn: A modeling study

“…Moreover, while there is much literature on epidemiological systems in the role of pathogen persistence and virulence selection in a variety of systems (e.g. Anderson and May, 1982; Dieckmann, 2002; Read and Mackinnon, 2008), the dynamics within a temporally explicit cohort structure have not been well studied (with the notable exception of a modeling study of coccidiosis in broiler chickens Klinkenberg and Heesterbeek (2007)). For these reasons, there is a dearth of information about how vaccination and strain virulence may alter the probability of an MD outbreak if barn contamination occurs.…”

Effect of Eimeria acervulina infection history on the immune response and transmission in broilers

“…Because the inoculated birds showed much higher oocyst excretion and elevated ␥␦TCR + T cell levels than the primed contact birds, this suggests that inoculation at day 24 of I NN and I NP birds resulted in a less effective protective immune response than the priming inoculation at day 6 of C NP birds. Apparently, there is a delay in the immune response, which may have considerable impact on dynamics in a larger population, and which is not yet covered by present models described by Klinkenberg and Heesterbeek (2007) and Severins et al (2007).…”

“…Most studies carried out in the last decades focused either on immunity (Lillehoj, 1988;Stiff and Bafundo, 1993;Williams, 1995) or epidemiology (Graat et al, 1998;Williams, 1998), but it is the mutual interaction between host and pathogen ("within-host dynamics"), and between infectious and susceptible hosts in a flock and the environment ("between-host dynamics") that determines the dynamics of the infection with the pathogen in a flock. Although this seems straightforward, the outcome of these interactions may give rise to non-linear effects, which may result in a counterintuitive and an unpredictable course of the infection Heesterbeek, 1995, 1998;Graat et al, 1996;Klinkenberg and Heesterbeek, 2007). Therefore, to provide more insight in the course of the disease coccidiosis in a flock, the dynamics of the immune reaction in individual hosts and transmission of the infection between hosts should be studied together.…”

A modeller's perspective on infection dynamics within and between hosts

“…However, in stables of broiler chickens, characterized by a dense population of susceptible hosts, the environmental contamination can quickly grow to levels where chickens ingest high doses of oocysts, causing severe outbreaks of clinical disease. The cleaning intensity between cohorts of broilers is thought to affect the number of clinical cases, yet studies trying to show this revealed counterintuitive results (Henken et al 1994;Graat et al 1996;Klinkenberg and Heesterbeek 2007). The model built in this project is used to understand the progression of infection in flocks of commercial broiler chickens and to assess if there exist cleaning regimes that minimize the clinical disease cases.…”

“…In infection processes where this is the case, studying infection at only one level may no longer be sensible or will no longer give realistic results (Mideo et al 2008). Several studies have shown the importance of models that include feedback loops between infection processes at different scales (Coombs et al 2007;Klinkenberg and Heesterbeek 2007;Boldin and Diekmann 2008). In many cases, these feedback loops that link the withinhost and between-host scale cause heterogeneity in the host population.…”